Guo Junxiong, Gu Shuyi, Lin Lin, Liu Yu, Cai Ji, Cai Hongyi, Tian Yu, Zhang Yuelin, Zhang Qinghua, Liu Ze, Zhang Yafei, Zhang Xiaosheng, Lin Yuan, Huang Wen, Gu Lin, Zhang Jinxing
School of Electronic Information and Electrical Engineering, Institute of Advanced Study, Chengdu University, Chengdu, 610106, China.
School of Integrated Circuit Science and Engineering, National Exemplary School of Microelectronics, University of Electronic Science and Technology of China, Chengdu, 610054, China.
Nat Commun. 2024 Jun 18;15(1):5193. doi: 10.1038/s41467-024-49592-4.
Multichannel meta-imaging, inspired by the parallel-processing capability of neuromorphic computing, offers considerable advancements in resolution enhancement and edge discrimination in imaging systems, extending even into the mid- to far-infrared spectrum. Currently typical multichannel infrared imaging systems consist of separating optical gratings or merging multi-cameras, which require complex circuit design and heavy power consumption, hindering the implementation of advanced human-eye-like imagers. Here, we present printable graphene plasmonic photodetector arrays driven by a ferroelectric superdomain for multichannel meta-infrared imaging with enhanced edge discrimination. The fabricated photodetectors exhibited multiple spectral responses with zero-bias operation by directly rescaling the ferroelectric superdomain instead of reconstructing the separated gratings. We also demonstrated enhanced and faster shape classification (98.1%) and edge detection (98.2%) using our multichannel infrared images compared with single-channel detectors. Our proof-of-concept photodetector arrays simplify multichannel infrared imaging systems and offer potential solutions in efficient edge detection in human-brain-type machine vision.
受神经形态计算并行处理能力启发的多通道元成像，在成像系统的分辨率增强和边缘辨别方面取得了显著进展，甚至延伸到中红外和远红外光谱范围。目前典型的多通道红外成像系统由分离光栅或合并多台相机组成，这需要复杂的电路设计和高功耗，阻碍了先进的类人眼成像器的实现。在此，我们展示了由铁电超畴驱动的可打印石墨烯等离子体光探测器阵列，用于具有增强边缘辨别的多通道元红外成像。通过直接重新调整铁电超畴的比例，而不是重建分离的光栅，所制备的光探测器在零偏置操作下表现出多个光谱响应。与单通道探测器相比，我们还利用多通道红外图像展示了增强且更快的形状分类（98.1%）和边缘检测（98.2%）。我们的概念验证光探测器阵列简化了多通道红外成像系统，并为类人脑机器视觉中的高效边缘检测提供了潜在解决方案。
